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title
Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion
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Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion
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Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion
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2026-03-10 00:21:01
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Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion Zipeng Fu * Xuxin Cheng * Deepak Pathak Carnegie Mellon University CoRL 2022 (Oral) Best Systems Paper Award Finalist (top 0.79%) Paper arXiv OpenReview Video Bilibili Poster Summary Code Whole-body control via a unified learned policy achieves agile and dynamic behaviors on our custom-built low-cost legged manipulator Abstract An attached arm can significantly increase the applicability of legged robots to several mobile manipulation tasks that are not possible for the wheeled or tracked counterparts. The standard control pipeline for such legged manipulators is to decouple the controller into that of manipulation and locomotion. However, this is ineffective and requires immense engineering to support coordination between the arm and legs, error can propa...
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